Functions, Classes, and Exceptions

You do not need advanced Python to solve most DSA problems, but you do need a few essentials.

Functions

def gcd(a, b):
    while b:
        a, b = b, a % b
    return a


print(gcd(18, 24))

Type hints

Type hints improve readability even when the interpreter does not enforce them.

from typing import List


def prefix_sums(nums: List[int]) -> List[int]:
    result = []
    running = 0
    for x in nums:
        running += x
        result.append(running)
    return result


print(prefix_sums([1, 2, 3, 4]))

Small classes

Classes matter most in DSA when we model nodes and custom structures.

class Node:
    def __init__(self, value):
        self.value = value
        self.next = None


head = Node(10)
head.next = Node(20)
print(head.value, head.next.value)

Exceptions

Raising a clear error is often better than silently returning the wrong result.

def top(stack):
    if not stack:
        raise IndexError("stack is empty")
    return stack[-1]


print(top([5, 7, 9]))

A practical rule

• Use functions for algorithms.
• Use classes for linked lists, trees, graphs, and reusable structures.
• Raise exceptions when an invalid operation should be explicit.